Pub Date : 2017-11-01DOI: 10.1109/ICSESS.2017.8342957
Yongjie Zhang, Yanyun Xu, Zheng Yang, Qin Sun
In order to obtain more accurate Lemaitre high cycle fatigue damage parameters, a BFGS quasi-Newton fitting method is proposed by optimizing the residual difference between the predicted life and actual life in the least square method. The damage parameters are solved in the damage evolution equation of metal high cycle fatigue. Taking 2A12-T4 aluminum alloy as an example, the precision and solution efficiency of BFGS quasi-Newton fitting method were verified for the evaluation of metal high cycle fatigue life.
{"title":"Study on BFGS fitting method of metal high cycle fatigue damage parameters","authors":"Yongjie Zhang, Yanyun Xu, Zheng Yang, Qin Sun","doi":"10.1109/ICSESS.2017.8342957","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342957","url":null,"abstract":"In order to obtain more accurate Lemaitre high cycle fatigue damage parameters, a BFGS quasi-Newton fitting method is proposed by optimizing the residual difference between the predicted life and actual life in the least square method. The damage parameters are solved in the damage evolution equation of metal high cycle fatigue. Taking 2A12-T4 aluminum alloy as an example, the precision and solution efficiency of BFGS quasi-Newton fitting method were verified for the evaluation of metal high cycle fatigue life.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127719655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSESS.2017.8343013
Binhan Xu, Shuyu Chen, Hancui Zhang, Tianshu Wu
The intrusion or attack in the computer network is one of the most important issues in Cloud environment. Due to enormous network traffic, dynamic and incremental learning is important to intrusion detection system (IDS) in Cloud. In existing incremental algorithms, k Nearest Neighbors (k-NN) has the advantage of dealing with the huge and incremental multi-class nature of data. However, k-NN algorithm has poor performance in classification. Support Vector Machine (SVM) is an extraordinary classification method widely used in intrusion detection field, while its training time increases sharply with expansion of training data. Therefore, we proposed Incremental k-NN SVM method using combination of k-NN and SVM, bringing advantages of the both methods. In this approach an R∗-tree provides efficient expansion of training data and query for k-NN. Experiments on open dataset KDDCUP 99 indicates that Incremental k-NN SVM intrusion detection method has the ability to learn and update with new data in acceptable time, and its predicting time does not increase rapidly along the incremental learning process.
{"title":"Incremental k-NN SVM method in intrusion detection","authors":"Binhan Xu, Shuyu Chen, Hancui Zhang, Tianshu Wu","doi":"10.1109/ICSESS.2017.8343013","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8343013","url":null,"abstract":"The intrusion or attack in the computer network is one of the most important issues in Cloud environment. Due to enormous network traffic, dynamic and incremental learning is important to intrusion detection system (IDS) in Cloud. In existing incremental algorithms, k Nearest Neighbors (k-NN) has the advantage of dealing with the huge and incremental multi-class nature of data. However, k-NN algorithm has poor performance in classification. Support Vector Machine (SVM) is an extraordinary classification method widely used in intrusion detection field, while its training time increases sharply with expansion of training data. Therefore, we proposed Incremental k-NN SVM method using combination of k-NN and SVM, bringing advantages of the both methods. In this approach an R∗-tree provides efficient expansion of training data and query for k-NN. Experiments on open dataset KDDCUP 99 indicates that Incremental k-NN SVM intrusion detection method has the ability to learn and update with new data in acceptable time, and its predicting time does not increase rapidly along the incremental learning process.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133764960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSESS.2017.8343032
B. Shan, D. Jia, Lu Zhang, Fang Cao, Yi Sun
The electric power alteration strategy can realize the substitution of the power supply for the coal and the fuel in the terminal energy consumption, which can realize the fundamental change of energy development mode. In this paper, to provide theoretical guidance for grid planning, energy demand forecasting model influencing factors in the context of electric power alteration are thoroughly analyzed, which concludes four key influence factors including environmental protection pressure restriction, energy price fluctuation, policy support and technical substitution. Combined all the factors, energy demand forecasting models in the context of electric power alteration including the Markal model(Market Allocation Model), LEAP model, MAED model(Model for Analysis of Energy Demand) are built, which can provide references for electric power alteration in China.
{"title":"Analysis of energy demand forecasting model in the context of electric power alteration","authors":"B. Shan, D. Jia, Lu Zhang, Fang Cao, Yi Sun","doi":"10.1109/ICSESS.2017.8343032","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8343032","url":null,"abstract":"The electric power alteration strategy can realize the substitution of the power supply for the coal and the fuel in the terminal energy consumption, which can realize the fundamental change of energy development mode. In this paper, to provide theoretical guidance for grid planning, energy demand forecasting model influencing factors in the context of electric power alteration are thoroughly analyzed, which concludes four key influence factors including environmental protection pressure restriction, energy price fluctuation, policy support and technical substitution. Combined all the factors, energy demand forecasting models in the context of electric power alteration including the Markal model(Market Allocation Model), LEAP model, MAED model(Model for Analysis of Energy Demand) are built, which can provide references for electric power alteration in China.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134021542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSESS.2017.8342875
R. R. Rani, D. Ramyachitra
The Cancer Feature Selection and classification problem is one of the prevalent tasks in computational molecular biology. Detecting a gene or list of genes which cause cancer can be acknowledged using the feature selection and classification which leads to giving a faultless treatment for patient and drug discovery of the particular gene. The feature selection and classification of cancer using microarray gene expression data is a computationally difficult task. Even now, the computation of gene selection and classification is a challenging area to provide an exact biological related gene that causes cancer. In this work, three methods have been proposed. One is the Fish Swarm Optimization algorithm along with both Support Vector Machine and Random Forest technique for cancer feature selection and classification. But the above methods have reduced very few features from the datasets. Thus, they are considered as an existing method for this work. Now, the second proposed method namely an enhanced Krill Herd Optimization (KHO) technique was employed for selecting the genes and Random Forest (RF) Technique was employed to classify the cancer types. The Random Forest classification has been used because of its accurate classification accuracy. First, the subset of features is selected using KHO and the Random Forest classification is applied to the selected features. Ten different gene microarray cancer datasets were used to evaluate the efficiency of the proposed. The proposed KHO/RF method is compared with other well-known existing methods like PSO/SVM, PSO/RF, FSO/SVM and FSO/RF. As an outcome, the proposed method outperforms the other existing methods with 100% accuracy of results for most datasets.
{"title":"Krill Herd Optimization algorithm for cancer feature selection and random forest technique for classification","authors":"R. R. Rani, D. Ramyachitra","doi":"10.1109/ICSESS.2017.8342875","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342875","url":null,"abstract":"The Cancer Feature Selection and classification problem is one of the prevalent tasks in computational molecular biology. Detecting a gene or list of genes which cause cancer can be acknowledged using the feature selection and classification which leads to giving a faultless treatment for patient and drug discovery of the particular gene. The feature selection and classification of cancer using microarray gene expression data is a computationally difficult task. Even now, the computation of gene selection and classification is a challenging area to provide an exact biological related gene that causes cancer. In this work, three methods have been proposed. One is the Fish Swarm Optimization algorithm along with both Support Vector Machine and Random Forest technique for cancer feature selection and classification. But the above methods have reduced very few features from the datasets. Thus, they are considered as an existing method for this work. Now, the second proposed method namely an enhanced Krill Herd Optimization (KHO) technique was employed for selecting the genes and Random Forest (RF) Technique was employed to classify the cancer types. The Random Forest classification has been used because of its accurate classification accuracy. First, the subset of features is selected using KHO and the Random Forest classification is applied to the selected features. Ten different gene microarray cancer datasets were used to evaluate the efficiency of the proposed. The proposed KHO/RF method is compared with other well-known existing methods like PSO/SVM, PSO/RF, FSO/SVM and FSO/RF. As an outcome, the proposed method outperforms the other existing methods with 100% accuracy of results for most datasets.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130358402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSESS.2017.8342910
Liu Hanyan, Wang Shihai, Liu Bin, X. Peng
Usually the complexity metric of software focuses on the complexity of code level, function level or structure level separately. It lacks of measurement for the comprehensive complexity of software system. This paper proposes a complexity metric model of three-level cascade network that based on complex network theory. In this metric model, the complexity of code level, function level and structure level are measured and the cascaded relationship between the three levels are analyzed. At last, the three-level cascade network model is built and the comprehensive complexity of software system is measured though the three-level cascade network model. The experiment result shows that the comprehensive complexity of the software system is correlated positively to the number of software defects.
{"title":"Software complexity measurement based on complex network","authors":"Liu Hanyan, Wang Shihai, Liu Bin, X. Peng","doi":"10.1109/ICSESS.2017.8342910","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342910","url":null,"abstract":"Usually the complexity metric of software focuses on the complexity of code level, function level or structure level separately. It lacks of measurement for the comprehensive complexity of software system. This paper proposes a complexity metric model of three-level cascade network that based on complex network theory. In this metric model, the complexity of code level, function level and structure level are measured and the cascaded relationship between the three levels are analyzed. At last, the three-level cascade network model is built and the comprehensive complexity of software system is measured though the three-level cascade network model. The experiment result shows that the comprehensive complexity of the software system is correlated positively to the number of software defects.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134257486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSESS.2017.8342988
Li Wei, S. Pei, Wang Wenjin, Y. Hao, Chen Zhuo, Sun Yi, Lin Bin
The terminal communication access network of power system is an information channel to guarantee the normal operation of the power grid, the rapid response of the fault, the efficient utilization of resources, the real-time transmission of the business and the sustainable production of electricity. For multi-layer networks, the use of single-layer survivability strategy may lead to the intensification of resource competition and the protection of the business, which requires the multi-layer network survivability strategy for inter-level coordination. In view of the current application status of multilayer communication bearer network, the survivability technology of multilayer network service carrier is researched, and the multi tier survivability network layer coordination is mainly studied.
{"title":"Research on survivability of multi-layer electric power service","authors":"Li Wei, S. Pei, Wang Wenjin, Y. Hao, Chen Zhuo, Sun Yi, Lin Bin","doi":"10.1109/ICSESS.2017.8342988","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342988","url":null,"abstract":"The terminal communication access network of power system is an information channel to guarantee the normal operation of the power grid, the rapid response of the fault, the efficient utilization of resources, the real-time transmission of the business and the sustainable production of electricity. For multi-layer networks, the use of single-layer survivability strategy may lead to the intensification of resource competition and the protection of the business, which requires the multi-layer network survivability strategy for inter-level coordination. In view of the current application status of multilayer communication bearer network, the survivability technology of multilayer network service carrier is researched, and the multi tier survivability network layer coordination is mainly studied.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134411513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSESS.2017.8342939
H. Sun, Xiling Luo, Yifu Xu
To solve the problem of large search space, large number of extended nodes, long searching time and large memory consumption for 3D path planning in general aviation(GA), this paper proposes an improved A∗ algorithm based on classical A∗ algorithm. The improved method first dynamically build 3D grid search space based on initial node and target node. Then nodes are extended by improving cost function, setting dynamic step length, and maintaining current flight state. Also optimize data structure to improve search efficiency. Finally, this paper has developed an application for real terrain that can be used to quickly and efficiently plan an optimized path.
{"title":"The research of path planning for general aviation based on improved A∗ algorithm","authors":"H. Sun, Xiling Luo, Yifu Xu","doi":"10.1109/ICSESS.2017.8342939","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342939","url":null,"abstract":"To solve the problem of large search space, large number of extended nodes, long searching time and large memory consumption for 3D path planning in general aviation(GA), this paper proposes an improved A∗ algorithm based on classical A∗ algorithm. The improved method first dynamically build 3D grid search space based on initial node and target node. Then nodes are extended by improving cost function, setting dynamic step length, and maintaining current flight state. Also optimize data structure to improve search efficiency. Finally, this paper has developed an application for real terrain that can be used to quickly and efficiently plan an optimized path.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131926524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSESS.2017.8342983
Benjamin Appiah, Eugene Opoku-Mensah, Zhiguang Qin
Web-Based applications are becoming more increasingly technically complex and sophisticated. The very nature of their feature-rich design and their capability to collate, process, and disseminate information over the Internet or from within an intranet makes them a popular target for attack. According to Open Web Application Security Project (OWASP) Top Ten Cheat sheet-2017, SQL Injection Attack is at peak among online attacks. This can be attributed primarily to lack of awareness on software security. Developing effective SQL injection detection approaches has been a challenge in spite of extensive research in this area. In this paper, we propose a signature based SQL injection attack detection framework by integrating fingerprinting method and Pattern Matching to distinguish genuine SQL queries from malicious queries. Our framework monitors SQL queries to the database and compares them against a dataset of signatures from known SQL injection attacks. If the fingerprint method cannot determine the legitimacy of query alone, then the Aho Corasick algorithm is invoked to ascertain whether attack signatures appear in the queries. The initial experimental results of our framework indicate the approach can identify wide variety of SQL injection attacks with negligible impact on performance.
{"title":"SQL injection attack detection using fingerprints and pattern matching technique","authors":"Benjamin Appiah, Eugene Opoku-Mensah, Zhiguang Qin","doi":"10.1109/ICSESS.2017.8342983","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342983","url":null,"abstract":"Web-Based applications are becoming more increasingly technically complex and sophisticated. The very nature of their feature-rich design and their capability to collate, process, and disseminate information over the Internet or from within an intranet makes them a popular target for attack. According to Open Web Application Security Project (OWASP) Top Ten Cheat sheet-2017, SQL Injection Attack is at peak among online attacks. This can be attributed primarily to lack of awareness on software security. Developing effective SQL injection detection approaches has been a challenge in spite of extensive research in this area. In this paper, we propose a signature based SQL injection attack detection framework by integrating fingerprinting method and Pattern Matching to distinguish genuine SQL queries from malicious queries. Our framework monitors SQL queries to the database and compares them against a dataset of signatures from known SQL injection attacks. If the fingerprint method cannot determine the legitimacy of query alone, then the Aho Corasick algorithm is invoked to ascertain whether attack signatures appear in the queries. The initial experimental results of our framework indicate the approach can identify wide variety of SQL injection attacks with negligible impact on performance.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132164392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSESS.2017.8342961
Guochao Lao, W. Ye, Guozhu Liu
The spaceborne synthetic aperture radar (SAR) image would become defocused and fuzzy when aiming to a moving vessel. To solve the problem, a vessel imagery enhancement method combining compressed sensing (CS) with time frequency distribution (TFD) is presented, by which, the imaging result is improved, and a series of images at different azimuth time are obtained showing the vessel posture changing. The validity of the method is verified by processing a measured SAR image.
{"title":"A vessel imagery enhancement method of spaceborne SAR based on CS-TFD","authors":"Guochao Lao, W. Ye, Guozhu Liu","doi":"10.1109/ICSESS.2017.8342961","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342961","url":null,"abstract":"The spaceborne synthetic aperture radar (SAR) image would become defocused and fuzzy when aiming to a moving vessel. To solve the problem, a vessel imagery enhancement method combining compressed sensing (CS) with time frequency distribution (TFD) is presented, by which, the imaging result is improved, and a series of images at different azimuth time are obtained showing the vessel posture changing. The validity of the method is verified by processing a measured SAR image.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133276473","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-01DOI: 10.1109/ICSESS.2017.8342967
Fadia Shah, Jianping Li, Y. Shah, F. Shah
The human life is always experiencing problems related to health. The survival is difficult if not treated well. For a better recovery, health problems are solved by treatment plans and medications; which are by health care professional called specialists, doctors or medical practitioners. Whatever these professionals recommend, it is well maintained in the form of reports. The collection of all this record makes Medical Big Data (MBD). Based upon the medical problem, this MBD includes medical history and prescription reports, test reports, X-Ray, CT Scan, and some other types of medical diagnosis. Traditional systems are now improved after the enhancements in telecommunication modes and innovation of smart devices with latest 5G technology has a huge contribution in every field of science. Regarding health care systems, in developed countries, E-Health and Telemedicine systems being developed to improve the quality of treatment. Such systems have many enhanced features like data management, reliable diagnoses; among them a distinct aspect is load reduction for the patient about data availability and management. Since MBD is increasing for every patient as the time passes and the patient consults again and again. Many schemes with efficient models are proposed to make this MBD available over the network by compression and network management tools. This exponential expansion of MBD has unmitigated the domains of MBD generating sources. In this paper, MBD collection, sources are discussed which ensure directly or indirectly how some domains are responsible to increase MBD more than normal ways.
{"title":"Extended definition of medical big data","authors":"Fadia Shah, Jianping Li, Y. Shah, F. Shah","doi":"10.1109/ICSESS.2017.8342967","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342967","url":null,"abstract":"The human life is always experiencing problems related to health. The survival is difficult if not treated well. For a better recovery, health problems are solved by treatment plans and medications; which are by health care professional called specialists, doctors or medical practitioners. Whatever these professionals recommend, it is well maintained in the form of reports. The collection of all this record makes Medical Big Data (MBD). Based upon the medical problem, this MBD includes medical history and prescription reports, test reports, X-Ray, CT Scan, and some other types of medical diagnosis. Traditional systems are now improved after the enhancements in telecommunication modes and innovation of smart devices with latest 5G technology has a huge contribution in every field of science. Regarding health care systems, in developed countries, E-Health and Telemedicine systems being developed to improve the quality of treatment. Such systems have many enhanced features like data management, reliable diagnoses; among them a distinct aspect is load reduction for the patient about data availability and management. Since MBD is increasing for every patient as the time passes and the patient consults again and again. Many schemes with efficient models are proposed to make this MBD available over the network by compression and network management tools. This exponential expansion of MBD has unmitigated the domains of MBD generating sources. In this paper, MBD collection, sources are discussed which ensure directly or indirectly how some domains are responsible to increase MBD more than normal ways.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"78 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133871328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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